Effects of 6-Month Sitagliptin Treatment on Metabolic Parameters in Diabetic Patients Taking Oral Glucocorticoids: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: There are no guidelines for the treatment of diabetes in patients taking glucocorticoids. We studied to understand the effects of 6-month treatment with sitagliptin on metabolic parameters in diabetic patients taking glucocorticoids. METHODS: We retrospectively picked up patients who had been prescribed sitagliptin for 6 months during the continuous prescription of oral glucocorticoids between October 2010 and October 2013 by a chart-based analysis, and compared the data before the sitagliptin treatment with the data at 6 months after the sitagliptin treatment started. RESULTS: Fifteen patients were eligible for the analyses in our study. The plasma glucose and HbA1c levels were significantly reduced by the sitagliptin treatment. Furthermore, body weight significantly decreased. We found a significant and inverse correlation between the change in HbA1c levels and HbA1c levels at baseline. However, there was no significant correlation between the change in HbA1c levels and the daily glucocorticoid dose at baseline. CONCLUSIONS: The present study demonstrated that sitagliptin significantly reduced plasma glucose, HbA1c and body weight. Further, sitagliptin was more effective to improve glycemic control in patients taking glucocorticoids with higher HbA1c levels, independently of the daily glucocorticoid dose.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".